Moving toward Rice Self-Sufficiency in Sub-Saharan Africa by 2030: Lessons Learnt from 10 Years of the Coalition for African Rice Development

The Coalition for African Rice Development (CARD) was initiated as policy framework with the aim of doubling rice production in sub-Saharan Africa (SSA) over the period from 2008 to 2018. This paper assesses the contribution of the CARD policy to rice production and forecasts the local rice supply and demand for a better understanding of the policies needed to attain rice self-sufficiency by 2030. A combination of the autoregressive integrated moving average method and counterfactual approach was adopted using rice statistical data from 23 countries in SSA. Results showed that the contribution of CARD to paddy rice production in 2018 was 10.2 million ton, equivalent to 74% of target. This resulted from the increasing of area and yield by 23% and 19%, respectively. However, yield growth rate was not sustainable in almost two-third of countries. Investments on supply-push factors such as fertilizer and irrigation development, which was the focus in the past, have less effect on the rice production. We conclude that sustainable investments on demand-pull factors such as private-led modern milling sector and contract farming development should be prioritized for achieving rice self-sufficiency in SSA.


INTRODUCTION
2013). In each country, NRDS was designed to provide support to and raise the productivity of the different rice production systems through targeted interventions (technologies, investments and capacity building) to different value chain actors (input dealers, farmers, millers, parboilers, traders and consumers). CARD policy framework was implemented in links to existing programs such as the Comprehensive Africa Agriculture Development Program (CAADP), the New Partnership for Africa's Development (NEPAD) and the Alliance for a Green Revolution in Africa (AGRA) (Golay, 2010). This paper aims to assess the contribution of the CARD policy framework to rice production over the period 2008 to 2018 of implementation and forecast local rice supply and demand to provide a better understanding of the policy measures necessary to achieve rice self-sufficiency by 2030. The contributions of the paper to the literature are threefold. First, we attempt to estimate the real contribution of policy measures to rice production. Although the impact of technologies is frequently discussed in the literature (Saito et al., 2019;Jiao and Schneeberger, 2017;Arouna et al., 2017;Kassie et al., 2011), the impact of policy measures is limited and to the best of our knowledge, this is the first attempt to estimate the impact of the CARD. We also analyze the determinants of the impact of CARD by considering both demand-pull and supply-push factors. Indeed, the NRDS plan considered both demand-pull and supply-push investments. However, the focus was mainly on supply-push investments (Demont, 2013). Therefore, it is important to analyze the contribution of this policy orientation. Second, this paper used a combination of the autoregressive integrated moving average (ARIMA) model and counterfactual approach to assess the impact of the CARD. Although extensive literature exists on the separate application of the ARIMA model (Ruby-Figueroa et al., 2017;Sen et al., 2016) and counterfactuals (Arouna et al., 2017;Manda et al., 2019), combination of the two methods is uncommon. Third, to determine the effort needed to achieve selfsufficiency in SSA, we forecasted rice production and consumption by 2030. Findings from this study will inform recommendations for policy makers and future research aimed at achieving rice self-sufficiency in SSA.

OVERVIEW OF THE CARD
In relation to the 2007-2008 food crisis, when the export price of rice exceeded US$ 1000 per ton (Pandey et al., 2010), rice sector development in SSA became crucial for food security. To close the local rice supply and demand gap, CARD policy framework was initiated in 2008 to promote rice sector development in 23 countries in Africa (Fig. 1). The main goal of the CARD policy framework was to double rice production, from 14 MT of paddy to 28 MT between 2008-2018 in SSA. To boost rice production, participating countries developed the first generation of national rice development strategies (NRDSs) (Demont, 2013) as policy documents for rice development in each country. A NRDS is a comprehensive strategy for achieving the rice development goal in a country. The formulation of the NRDSs was led by national Electronic copy available at: https://ssrn.com/abstract=3684527 institutions and subjected to a broad policy-based dialog and consultation with the active participation of relevant stakeholders in the rice value chain. Each NRDS referenced the global rice sector and that the focus was on short-, medium-and long-term actions. As a result, 23 African countries have subsequently developed NRDS documents that are available on the CARD web portal 2 . The NRDSs were designed to respond to different issues faced in the rice value chain development, such as the lack of appropriate policies, weaknesses in policy research and planning for increased rice production, the lack of availability of and access to quality seeds and production inputs (fertilizers, herbicides, etc.), the lack of irrigation schemes, difficulties in water management and weakness in agricultural extension systems. Although the major focus of the NRDSs was on investments for production increase, some attention to value-added investments and value chain upgrading was noted (Demont, 2013). Through the implementation of the NRDSs, the main actions taken to achieve the CARD goal were (1) yield-enhancing technical package distribution, (2) on-farm demonstration plots, (3) the introduction and distribution of small-and mediumscale rice processing equipment, (4) high-level advocacy measures, and (5)  Agency (JICA). The total investments in the projects are estimated to be approximately US$ 9 billion (CARD, 2019) 3 . With achievement of the set target, CARD entered its second phase in 2019, with a new target of further doubling annual rice production in SSA, from 28 MT to 56 MT, by 2030. Nine countries, two development partners and five Regional Economic Communities newly joined the initiative.

Impact assessment approach
The CARD aimed to increase rice production from 14 MT in 2008 to 28 MT in 2018. To assess the level of achievement of this objective, the trends in rice yield, area and production from 2008 to 2018 were calculated. The growth rates of the decades before and after the 2007-2008 food crisis (1996-2007 and 2008-2018) were also computed and analyzed.
Although the trend analysis allowed us to assess the achievements of the CARD policy objective, it did not allow us to quantify the impact or net effect of the CARD on rice production statistics (production, yield and area) and self-sufficiency. To estimate the CARD impact, we used the counterfactual framework.
The true impact of the CARD is the difference between the observed situation (situation with CARD) and the situation that would have happened if the CARD policy framework did not act (counterfactual situation).
The counterfactual situation represents the status of a country had it not participated in the CARD. However, the availability of counterfactual data to estimate the net effect of an intervention is often the most Electronic copy available at: https://ssrn.com/abstract=3684527 challenging part of impact analysis. One cannot observe the counterfactual situation of the CARD countries because all countries participated through differing actions. To address this known missing data in the counterfactual framework (Anderson et al., 2016), we simulated the counterfactual situation.
We employed the ARIMA model, which is a time series model largely used in the literature to forecast the future or to predict missing values (Hassani et al., 2009;Wang et al., 2018). The ARIMA model performed similarly in forecasting as other models, such as the singular spectrum analysis technique and the Holt-Winters' model (Hassani et al., 2009). Using the ARIMA model, we generated the counterfactual situation by forecasting the values of the yield and area from 2008 to 2018 based on the historical trends from 1960 to 2007.

Yield and area impact estimation model
The impacts of the CARD on area and yield in year were expressed as follows: where ∇ and ∇ denote the impact of the CARD policy on area and yield in year , respectively.
, and , represent the observed value of the area and yield in year , respectively, and , and , are the counterfactual situation of the area and yield in year in the absence of implementation of the CARD.

Production impact estimation model
The change in rice production can be through the increase of the rice productivity per unit of land and through the expansion of the rice harvested area (You et al., 2011). The impact of the CARD on production could be related to (i) a change in yield only, (ii) a change in area only, and (iii) a contribution to changes in yield and area. This is equivalent to the sum of the product of the observed area and the impact on the yield and the impact on the area and the yield in the counterfactual. This impact was derived as follows (for simplicity, the index t is not spelled out): where ∇ is the impact on rice production, and the other parameters are as defined in equations 1 and 2.
The determinants of CARD impact of paddy production were modelled using simple ordinary least squared regressions. Two categories of variables were considered: supply-push factors and demand-pull factors.
Four variables were considered as supply-push factors in the final model: number of varieties release or adopted, fertilizer used per hectare, number of extension agents and share of irrigated area. Importance of investments on value chain upgrading and dominance of preference for local were considered as demand- including number of projects focusing on either seed and paddy production or post-harvest were considered but they did not improve the quality of the model.

Self-sufficiency impact estimation approach
The production to consumption ratio was used as an indicator of self-sufficiency (van Oort et al., 2015).
We calculated the impact on self-sufficiency in terms of the annual contribution of the CARD to selfsufficiency. The annual contribution of the CARD to self-sufficiency is given by the following equation: where ∇ is the impact of the CARD on rice self-sufficiency, is the observed consumption, and ∇ is the impact on rice production.

ARIMA model estimation procedure
In forecasting, the ARIMA model is a commonly used approach (Wang et al., 2018). The ARIMA model is a time series model that forecasts variables. The model uses information from the variable itself to forecast its trend. Each variable in the series is forecasted by using its historical values. To fit a time series ARIMA model, stationarity is a necessary condition. The stationarity of the time series implies that the mean and variance of the series are constant. When the time series is nonstationary, it is differenced to make it stationary. After the stationarity of the series is verified, the ARIMA fitting model is run to identify the stochastic process of the time series and to forecast the future values accurately. The process is referred to as ARIMA (p, d, q), where p and q are the order of the autoregressive (AR) and moving-average (MA) models, respectively, and d refers to the order of differencing required to make the series stationary. The ARIMA model follows four steps: identification, estimation of parameters, diagnostic checking and forecasting (Hassani et al., 2009;Wang et al., 2018).

Forecast of rice production and consumption by 2030
Forecasting is a means for better understanding the effort needed to meet rice self-sufficiency goals. To align with the Sustainable Development Goals (SDGs) period, which is also the target year of the second Electronic copy available at: https://ssrn.com/abstract=3684527 phase of CARD, the forecast horizon of 2030 was chosen. The ARIMA model was also used to forecast the annual rice consumption by 2030 using the historical trend from 1960 to 2018.
Forecasting rice production by 2030 is based on the potential area and attainable yield. In terms of the area, there is still a considerable amount of suitable land for rice cropping. The potential area is estimated to be more than 190 million ha (MHa) of inland valley in SSA (Deininger et al., 2011;Rodenburg et al., 2014), of which approximately 12% is used in 2018 (USDA, 2019) 4 . From this, we estimated the potential area for rice in the CARD countries to be more than 101 million ha. Yield gaps exists in many African countries, and yield represents on average 40% of its potential in 2018 (van Oort et al., 2015). The attainable yield would be on average 6 t/ha with 8 t/ha, 6 t/ha and 4 t/ha in irrigated, lowland and upland ecology, respectively (Seck et al., 2010). We forecasted rice production based on the potential yields and area in SSA and the CARD countries.
To predict rice production, we employed three scenarios based on uses of area and potential yield levels. The first scenario of future rice production assumed that the average growth rate in yield and area in CARD countries over the period 2008-2018 would continue. This is equivalent to 2.6% and 4.5% growth in yield and area, respectively, and represents the baseline. The second scenario was an optimistic scenario and corresponded to an increase of yield and area by about 20% compared to the baseline. This is equivalent to an annual increase in yield of 3% and area of 5.5% and it was related to the additional effort required by the second phase of the CARD to boost rice production for self-sufficiency. The third scenario was a pessimistic scenario related to a decline in rice productivity due to yield limiting and reducing factors (higher incidence of pests, diseases, droughts, floods and climate change) and socioeconomic issues such as the current corona virus disease  pandemic. This scenario supposed 1% and 2% growth in yield and area, respectively, representing about 60% yield and area growth decrease compared to the baseline. Rice is grown in various environments (mainly upland, rainfed lowland and irrigated) but due to data availability the analysis could not perform for each environment.

Data
The data used are from the United States Department of Agriculture (USDA) and FAO database (FAOSTAT), which are the two largest available databases on agricultural production in the world. The main database used was the USDA because it entirely covered the period of interest from 2008-2018 5 . In addition, the FAOSTAT was used for four countries (Ethiopia, Zambia, the Central African Republic and Rwanda). The production data for the Central African Republic and Ethiopia were not available from the USDA, while the data for Zambia and Rwanda were only available up to 2013 on the USDA.

Trends in rice production from 1996 to 2018
This section compares the rice production statistics (harvested area, yield and production) trends between the decades before and after the 2007-2008 food crisis (1996-2007 and 2008-2018). A continuous increase in rice harvested area was observed in the CARD countries from 1996 to 2018 (Fig. 2). However, the higher slope in the rice harvested area was observed after 2008 and was mainly driven by the West Africa 6 . During the decade before 2008, the harvested area increased by 19% (6.4 to 7.6 MHa from 1996-2007) in contrast to the 60% increase (7.6to 12.2 MHa) between 2008 and 2018. Regional analysis revealed that West Africa had the highest increase of 70% (4.9 to 8.3 MHa), followed by East Africa at 44% (2.2 to 3.2 MHa) and Central/southern Africa at 35% (0.5 to 0.7 MHa).

Fig. 2. Trend in rice harvested area in the CARD countries (1000 ha)
The yield increased more rapidly during the 2008-2018 decade but was less than the area increase ( Fig. 3 Mozambique, and Togo) showed, however, continuous yield growth increase between the two periods.
Using annual public expenditure in agriculture as proxy of annual expenditure in the rice sector, we found that the growth rate of investment in agriculture per hectare decreases from 3.28% between 2008-2012 to 0.91% after 2012 (Fig. 4). This shows that public investment in agriculture was not sustainable after the food crisis which have had negative impact on the yield of crops such as rice.    Similar to the harvested area and yield, the rice production showed a continuous increase since 1996 (Fig. 5). However, the increase was the highest over the last decade in the CARD participating countries. Rice production increased by 103% (13.7 to 27.9 MT from 2008-2018) in contrast with an increase of 31% from 1996-2007. This is also shown by higher slope of the linear trends of the production during the period 2008-2018 ( Figure 5). Rice production increased by 2.03 times during the CARD period.
This aligned with the overall CARD objective of doubling rice production in SSA between 2008-2018.
However, the achievement varied between regions and countries. West Africa showed an increase of 143% (7.8 to 19.0 MT); Central/southern Africa, 54% (0.4 to 0.7 MT); and East Africa, 50% (5.5 to 8.2 MT). Only 7 countries (Cameroon, Ghana, Kenya, Senegal, Cote d'Ivoire, Benin and Tanzania) achieved the CARD objective of doubling rice production by 2018. However, the comparison of before and after the food crisis may not reveal the real impact of the CARD. In reality, the time effect will bias the before-after comparison. Without the CARD, trends in rice statistics would have changed over the decades. The next section will attempt to more robustly estimate the contribution of the CARD to rice production growth in the 23 countries.

Impact on rice harvested area and yield
Using the ARIMA model, the counterfactual scenarios (the trends of the harvested area and yield if there had been no CARD policy framework) were computed 7 to estimate the real impact of CARD. The results showed that the estimated impact of the CARD on rice harvested area was on average 1.7 MHa per year ( Fig. 6 and Table A.1 in Appendix). The impact has continuously increased over time especially from 2010, 7 ARIMA (4, 2, 0) and ARIMA (1,1,0) had the best fits for the harvested area and yield, respectively.

Fig. 6. Comparison of the harvested area with the CARD and the counterfactual scenario
Although the trend was different, a similar positive impact was estimated for the yield (Fig. 7). The impact on yield was 0.29 t/ha per year (Table A.1 in Appendix). However, the impact on yield varied from year to year. The highest impact was 0.41 t/ha in 2018, representing 19% of observed yield.

Impact of the CARD on paddy production and self-sufficiency
Figs. 8 and 9 show respectively the trends in the actual production and rice self-sufficiency values and the counterfactual scenarios. The counterfactual values of production were below the observed values, meaning that the impact of the CARD on production was positive and consequently the effect on rice self-sufficiency was also positive. The annual impact of the CARD on production was estimated on average at 6.2 MT of paddy rice (Table A   Kenya, Rwanda, Uganda and Zambia) were classified into the third group, and one country (the Central African Republic) was in the fourth group. Impact at country level revealed that the higher the production in a country, the higher the impact on total production. However, when estimating the relative production increase due to CARD (Table A.2 in Appendix), the performances of Tanzania and Mali in the first group (50% and 42%, respectively) were lower than in Mozambique and Zambia in the third group (98% and 66%, respectively). Self-sufficiency without CARD Self-sufficiency with CARD Fig. 10. Grouping of countries based on CARD Impact on production

Determinants of CARD contribution on rice production
Determinants of CARD impact in countries were investigated using simple ordinary least square regression.
The model is globally significant at 5% and the R-squared is high (64%). Robust standard errors are reported to avoid any heteroskedasticity problem. The Variance Inflation Factors (VIF) showed that multicollinearity is not a problem in the model.
Results showed that investments on demand-pull factors have a stronger effect on the contribution of CARD to production than the supply-push factors ( for local rice is positive and significant. This means that the impact of CARD was higher in coastal countries with preference for local rice compare to landlocked countries. The coefficient of number of varieties release or adopted was also significant at 1% level. However, its marginal effect (0.018 MT of paddy rice per year) was lower than the marginal effect of three variables related to demand-pull factors. Moreover, the effect of two other supply-push factors (quantity of fertilizer per hectare and the share of irrigated area) were not significant. This showed the relative importance of demand-pull investments compare to supplypush investments for achieving rice self-sufficiency.  https://strasa.irri.org/varietal-releases (accessed 17 July 2020). ϒ Investment in value chain upgrading is based on the groups defined by Soullier et al. (2020) and the third group of "no evidence of upgrading investment" is the reference group. Ϯ The reference group is "Landlocked country" following Demont (2013). The dependent variable is the cumulative impact of CARD per country and expresses in 1000 ton.

Rice production and self-sufficiency by 2030
Rice consumption was forecasted by 2030 using the ARIMA model (Fig. 11) 9 . The results showed that the consumption was expected to reach approximately 49.2 MT of milled rice by 2030 in the 23 countries 10 in contrast with a total consumption of 30.6 MT of milled rice in 2018.
We developed scenarios for production and consumption by 2030. With the first scenario being business as usual (the baseline) with an annual increase in yield of 2.6% and area of 4.5%, the total production would be approximately 40.1 MT by 2030. This will lead to a consumption-production gap of 9 ARIMA (1,2,1) was the best fits for rice consumption (Fig. A.3. in Appendix).
approximately 9 MT of milled rice to be imported from Asia or Americas. This would likely cost approximately US$ 5.8 billion per year. To reduce this importation bill and achieve rice self-sufficiency, an optimistic scenario was plausible (Fig. 11). The optimistic scenario with a high annual increase in yield of 3% and area of 5.5% (increase by approximatively 20% of yield and area compared to the baseline) would result in a production equivalent to 49.2 million tons of milled rice and would help to achieve selfsufficiency by 2030. This is theoretically achievable because this scenario is equivalent to the use of 54% of the potential yield and 23% of the potential area by 2030 compared to the 40% and 12% of the potential yield and area respectively, in 2018. The low-increase scenario (pessimistic scenario) supposed that yield and area would increase less than what was observed in the last decade (1% and 2% growth rates in yield and area, respectively). In this scenario, production would be approximately 25.9 MT of milled rice, leading to 50% import dependency.  (Seck et al., 2010;Saito et al., 2015). However, the yield growth was not sustainable throughout the CARD period. despite the commitment of African leaders to allocate at least 10% of the total government expenditure to the agriculture sector. Sustainable yield growth requires long term development actions (Binswanger and Deininger, 1997).
The impact assessment of the CARD showed, that over the period of implementation, 74% of the objective of doubling rice production in 2018 was achieved. The impact was higher in West African countries than those in East Africa except for Tanzania. This result can be explained by the fact that rice consumption is more rapidly increasing in West Africa than any other part of SSA (Soullier et al., 2020).
Central African Republic had negative impact and it is explained mainly by the security crisis in the country since 2013. The results showed that the contribution of CARD is significantly determined by investments on demand-pull factors through investments in value chain upgrading. The higher the investments on value chain upgrading the higher the impact of CARD policy. This implies that investments in value chain upgrading through modern mills development and vertical coordination were able to increase the rice paddy production. Modern mills require high quantity of paddy to reach profitability and to recover the investments. Therefore, modern mill owners also invested directly in the production through vertical integration or indirectly through contract farming which was found to have also positive impact on production . This result confirms the findings of Demont (2013) who argued that more resources need to be provided for value-addition and demand-pull investment in the rice sector in SSA.
However, value chain upgrading is still marginal in SSA. Soullier et al. (2020) found that only Senegal and Nigeria can be considered as dynamic in value chain upgrading in West Africa during the CARD period.
As it was the case in Senegal and Nigeria, value chain upgrading in SSA should be private led for sustainability and efficiency in management. Due to the low share of demand-pull investments in the first generation of the NRDS in many countries (Demont, 2013), more resources will need to be allocated to private-led value chain upgrading during the second phase of CARD to achieve self-sufficiency by 2030.
The results showed that, among supply-push factors, only the number of high-yielding varieties release and adopted has positive effect on CARD impact. Improved high-yielding varieties are important not only for productivity growth but also for cropping systems adaptation to climate change and other stresses (iron-toxicity, salinity, etc.) (van Oort, 2018). Arouna et al. (2017) showed that improved rice varieties affect positively productivity and production. Surprisingly, the effect of inorganic fertilizer on production growth during the CARD period was not significant. This may be explained by two main factors.
First, SSA is characterized by low use of fertilizer (Sheahan and Barrett, 2017;MacCarthy et al., 2018) in conjunction with bush burning, residual removal from the field, disappearing fallows, high levels of deforestation, land degradation and nutrient depletion indicated non-sustainable land use. Although there is heterogeneity between countries and within countries for the use of fertilizer, the current farmer level of inorganic fertilizers use cannot allow to realize the potential yield gain. The efficiency of inorganic fertilizers required the use of organic fertilizers and improved germplasm along with good agricultural practices (Vanlauwe et al., 2015) and also water management. Second, blanket fertilizer recommendations are the general approach in many countries in SSA. Blanket fertilizer recommendations do not consider the variation in local settings but is rather uniform in space and time (MacCarthy et al., 2018). Failure to formulate fertilizer recommendations that is soil-and crop-specific and that considers the effect of climate variability results in inefficiency in fertilizer use. Therefore, the use of inorganic fertilizer based on blanked recommendation throughout the CARD period does not allow to achieve the expected yield gain. However, new applications such as RiceAdvice or Crop Manager that can deliver target recommendations are increasingly available and are expected to increase the efficiency of inorganic fertilizer .
Share of irrigated areas has no effect on the impact of CARD. Many investments in irrigation schemes have failed to deliver the anticipated benefits (Byiringo et al., 2020). Many schemes fail for lack of collective action over basic maintenance issues and absence of a coordination mechanism to allocate water across users in the system. In addition, inefficient irrigation systems are the major problems in rice irrigation ecology (Fahad et al., 2019). Therefore, sustainable rice production in existing irrigation schemes required collective action and coordination for maintenance.
To match consumption by 2030, production needs to increase by 2.7 times the 2018 level, indicating that an important investment will be needed to achieve rice self-sufficiency by 2030. Policy measures leading to annual increases in yield and area by 3% and 5.5%, respectively, would allow self-sufficiency to be achieved by 2030. Most African governments are implementing the National Agriculture Investment Plan (NAIP) and the second phase of the CARD. However, to achieve rice self-sufficiency, it is important to identify the proper areas for investment. Priority area of interventions should be investments on private-led value chain upgrading through modern mills development and contract farming as well as improved varieties release and seed systems developments. We recognize however that ecology-specific recommendations would be more useful if data were available to analyze the contribution of CARD per growing environment.

CONCLUSION
This study assessed the contribution of the CARD through the analysis of the situation of rice production before and after the CARD implementation and the estimation of the impact of the CARD on the rice harvested area, yield, production and self-sufficiency using a combination of the ARIMA model and the counterfactual framework. The results indicated that rice production increased more during the CARD decade than during the previous decade. The CARD increased rice production in participating countries.
The experience of the CARD revealed that policy measures designed and implemented effectively will generate progress in rice sector development for self-sufficiency and food security in SSA. However, yield growth was not sustainable throughout the CARD period due to the relaxation in government investment after 2012.
Although local rice production increased rapidly after the 2008 food crisis, it has never caught up with demand. Considering the results of the CARD, the goal of self-sufficiency achievement requires policy measures to be implemented in a sustained and efficient manner and in the long term. Scenario analysis showed that annual increases of 3% and 5.5% in yield and area, respectively, would lead to the achievement of self-sufficiency by 2030. Based on the lesson learnt from the CARD, value chain upgrading through private investments in modern mills sector as well as operational vertical coordination should be the priority for sustainable rice production growth to achieve rice self-sufficiency in SSA.